




"""simple docstring"""




from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase				:     Tuple					=				logging.get_logger(__name__)

lowerCAmelCase				:     Tuple					=				{
    """microsoft/markuplm-base""": """https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json""",
    """microsoft/markuplm-large""": """https://huggingface.co/microsoft/markuplm-large/resolve/main/config.json""",
}






class        __magic_name__				(			UpperCAmelCase__							):






				'''simple docstring'''
				__UpperCamelCase         =		"markuplm"





				def __init__(			self						,					_a=30_522						,					_a=768						,					_a=12						,					_a=12						,					_a=3_072						,					_a="gelu"						,					_a=0.1						,					_a=0.1						,					_a=512						,					_a=2						,					_a=0.02						,					_a=1e-1_2						,					_a=0						,					_a=0						,					_a=2						,					_a=256						,					_a=1_024						,					_a=216						,					_a=1_001						,					_a=32						,					_a=50						,					_a="absolute"						,					_a=True						,					_a=None						,					**_a						,					):





							"""simple docstring"""
							super().__init__(
							    pad_token_id=_a						,					bos_token_id=_a						,					eos_token_id=_a						,					**_a						,					)
							lowerCamelCase      =   vocab_size
							lowerCamelCase      =   hidden_size
							lowerCamelCase      =   num_hidden_layers
							lowerCamelCase      =   num_attention_heads
							lowerCamelCase      =   hidden_act
							lowerCamelCase      =   intermediate_size
							lowerCamelCase      =   hidden_dropout_prob
							lowerCamelCase      =   attention_probs_dropout_prob
							lowerCamelCase      =   max_position_embeddings
							lowerCamelCase      =   type_vocab_size
							lowerCamelCase      =   initializer_range
							lowerCamelCase      =   layer_norm_eps
							lowerCamelCase      =   position_embedding_type
							lowerCamelCase      =   use_cache
							lowerCamelCase      =   classifier_dropout
							# additional properties
							lowerCamelCase      =   max_depth
							lowerCamelCase      =   max_xpath_tag_unit_embeddings
							lowerCamelCase      =   max_xpath_subs_unit_embeddings
							lowerCamelCase      =   tag_pad_id
							lowerCamelCase      =   subs_pad_id
							lowerCamelCase      =   xpath_unit_hidden_size









"""simple docstring"""




import os
from collections import namedtuple

import pytest

from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict


lowerCAmelCase				:     Dict					=				namedtuple(
    """_TestCommandArgs""",
    [
        """dataset""",
        """name""",
        """cache_dir""",
        """data_dir""",
        """all_configs""",
        """save_infos""",
        """ignore_verifications""",
        """force_redownload""",
        """clear_cache""",
    ],
    defaults=[None, None, None, False, False, False, False, False],
)



def        a__					(							snake_case__			,					snake_case__							)		->   Optional[Any]:
			return (abs(source - target							) / target) < 0.01



@pytest.mark.integration
def        a__					(							snake_case__							)		->   int:
			lowerCamelCase      =   _TestCommandArgs(dataset=snake_case__			,					all_configs=snake_case__			,					save_infos=snake_case__							)
			lowerCamelCase      =   TestCommand(*snake_case__							)
			test_command.run()
			lowerCamelCase      =   os.path.join(snake_case__			,					"""README.md"""							)
			assert os.path.exists(snake_case__							)
			lowerCamelCase      =   DatasetInfosDict.from_directory(snake_case__							)
			lowerCamelCase      =   DatasetInfosDict(
			    {
			        """default""": DatasetInfo(
			            features=Features(
			                {
			                    """tokens""": Sequence(Value("""string"""							)							),
			                    """ner_tags""": Sequence(
			                        ClassLabel(names=["""O""", """B-PER""", """I-PER""", """B-ORG""", """I-ORG""", """B-LOC""", """I-LOC"""]							)							),
			                    """langs""": Sequence(Value("""string"""							)							),
			                    """spans""": Sequence(Value("""string"""							)							),
			                }							)			,					splits=[
			                {
			                    """name""": """train""",
			                    """num_bytes""": 2_35_15_63,
			                    """num_examples""": 1_00_00,
			                },
			                {
			                    """name""": """validation""",
			                    """num_bytes""": 23_84_18,
			                    """num_examples""": 10_00,
			                },
			            ]			,					download_size=3_94_06_80			,					dataset_size=2_58_99_81			,					)
			    }							)
			assert dataset_infos.keys() == expected_dataset_infos.keys()
			for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
						lowerCamelCase ,  lowerCamelCase      =   getattr(dataset_infos["""default"""]			,					snake_case__							), getattr(expected_dataset_infos["""default"""]			,					snake_case__							)
						if key == "num_bytes":
									assert is_apercent_close(snake_case__			,					snake_case__							)
						elif key == "splits":
									assert list(snake_case__							) == list(snake_case__							)
									for split in result:
												assert result[split].name == expected[split].name
												assert result[split].num_examples == expected[split].num_examples
												assert is_apercent_close(result[split].num_bytes			,					expected[split].num_bytes							)
						else:
									result == expected



